Senior Manager, Machine Learning Operations (Perception)
$180k - $247.5kFull-time
Symbotic LLC
Who We Are With its A.I.-powered robotic technology platform, Symbotic is changing the way consumer goods move through the supply chain. Intelligent software orchestrates advanced robots in a high-density, end-to-end system – reinventing warehouse automation for increased efficiency, speed and flexibility. What We Need Symbotic is currently seeking an experienced leader to join our team. The Senior Manager, Machine Learning Operations (ML Ops) within the Perception team leads the development, scaling, and reliability of the ML lifecycle supporting robotic perception systems. This role oversees data pipelines, deployment infrastructure, and monitoring systems, working closely with perception algorithm and controls teams to ensure robust, scalable performance of models across large fleets of robots and warehouse environments. What We Do The Perception team is part of the Software Engineering organization which is responsible for building and delivering the intelligent robotic software platform that powers Symbotic’s automation systems. The team develops and operates perception and machine learning systems that enable robots to understand and interact with complex warehouse environments, supporting safe, efficient, and scalable operations across customer sites. What You'll Do
- Drives the development and scaling of ML Ops infrastructure, including data pipelines, model training and validation workflows, deployment systems, and monitoring frameworks.
- Coordinates cross-functional efforts with perception, controls, and platform teams to ensure seamless integration of ML models into production robotic systems.
- Leads end-to-end ML lifecycle processes, including dataset management, model versioning, release processes, and production validation across distributed fleets.
- Manages and mentors a team of ML and data engineers, fostering a high-performing, collaborative, and execution-focused team environment.
- Ensures high-quality, reliable delivery of ML-enabled functionality by establishing best practices in reproducibility, observability, and operational excellence.
- Drives continuous improvement of monitoring systems, including software and hardware telemetry, to support system performance, diagnostics, and maintenance operations.
- Requires a Bachelor’s Degree in Computer Science, Computer Engineering, Robotics, or a related field; Master’s Degree preferred or equivalent work experience.
- Minimum of 10+ years of experience in software engineering, machine learning systems, or infrastructure development.
- Minimum of 3+ years of experience managing or leading engineering teams in ML, data, or infrastructure domains.
- Strongly preferred{{:}} Experience building and scaling ML Ops platforms, including data pipelines, model deployment systems, and monitoring and observability tools.
- Required technical skills{{:}} Proficiency in Python and/or C++; experience with distributed systems and cloud platforms (e.g., GCP), containerization (Kubernetes), and data/streaming technologies (Kafka, Snowflake). Experience with analytics and visualization tools (e.g., Tableau) is preferred.
- Competencies{{:}} Strong cross-functional leadership, execution focus, communication skills, and the ability to drive process maturity in complex, fast-paced engineering environments.
- Up to 10% of travel may be required. Employees must have a valid driver’s license and the ability to drive and/or fly to client and other customer locations.
- The employee is responsible for owning a credit card and managing expenses personally to be reimbursed on a bi-weekly basis.
Vacancy posted a month ago
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